bgns: Biweight Graph and Network Statistics

Provides memory-efficient biweight midcorrelation and exact bicor-based k-nearest-neighbor graph construction for dense and sparse numeric matrices. Dense, sparse, and mixed-input paths avoid materializing full dense similarity matrices for tidy and k-nearest-neighbor workflows where possible. The implementation supports pairwise finite-overlap handling and robust correlation-based graph construction for biological expression matrices and other high-dimensional numeric data.

Version: 0.4.3
Depends: R (≥ 4.3.0)
Imports: Matrix, methods, stats
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2026-09-27
DOI: 10.32614/CRAN.package.bgns (may not be active yet)
Author: Aditya Kshirsagar [aut, cre]
Maintainer: Aditya Kshirsagar <adityaksh4 at gmail.com>
BugReports: https://github.com/metaddict/bgns/issues
License: GPL-3
URL: https://github.com/metaddict/bgns
NeedsCompilation: yes
SystemRequirements: C++17, optional OpenMP
Citation: bgns citation info
Materials: README, NEWS
CRAN checks: bgns results

Documentation:

Reference manual: bgns.html , bgns.pdf
Vignettes: bgns: Biweight Graph and Network Statistics (source, R code)

Downloads:

Package source: bgns_0.4.3.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: bgns_0.4.3.zip
macOS binaries: r-release (arm64): bgns_0.4.3.tgz, r-oldrel (arm64): bgns_0.4.3.tgz, r-release (x86_64): bgns_0.4.3.tgz, r-oldrel (x86_64): bgns_0.4.3.tgz

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